With advancing computer technologies, computer users have become more and more interested, and demand has grown for, interactive functions and improved data processing and manipulation for a variety of tasks of varying complexity. There has been growth, and interest in furthering of capability, in areas such as analytic processing of data. These technologies have increased execution rates for text recognition, content match, and information retrieval functions. Data that can take users further abounds within countless data sources. Similarly, the number of devices with the potential to call upon those data sources has multiplied exponentially. Pieces of data, such as specific words or phrases, can be matched, recognized and brought to the attention of a user with increasing velocity and frequency.
Moreover, current compute technologies are facilitating human interaction via an increasing variety of digital communication platforms such as e-mail, social media, and e-publishing, which can be accessed and executed via a number of devices including PCs, tablets, laptops and smartphones.
However, while some of these technological functions have been employed for decades, the user experience with both computer processing and digital communications can still be somewhat random and falls short in delivering the user information that could assist or inform them when they need it. Accordingly, these technologies have not met their potential. Even with unprecedented access to data, digital communications fail to make full use of available and relevant information.
Users typically obtain needed information by typing searches into search) engines, (e.g. Google™), or other systems or platforms such as an online or desktop database. However, this method depends on the user knowing what it is they do not know, what they need to know, and knowing enough to form and execute a correct search. However, that a user is searching a topic is itself a self-evident indication that they may not have knowledge of that area, such that they may not know what they need to know or search for. In other words, the user may have a situation in which, to use an expression, they “Don't know what they don't know” about any given topic. This can result in large knowledge gaps, underinformed or even misinformed users, wasted time searching, and inconsistent or incorrect search results.
This failure can also be attributed at least partly to the extra effort required for people to actively seek out relevant detail for communications support, such as additional reading or research. Users may not have the extra time for such research, or may not see it as a priority compared to other items. Further, readers may not explore or gather and organize data in an area because users, not knowing the information, do not know its importance.
Accordingly, as users work with data, for example while writing a document or creating a spreadsheet, it is possible, or even likely, the user will have knowledge gaps with their subject matter, because they do not have time to close the gap, underestimate the importance of the gap, or are unaware the gap exists.
Users generally only search for information associated with a key term (record) they are typing or reading when the user has a knowledge gap the user is aware of, or when communication circumstances are critical enough that validation of information is required. The result is that communication often lacks the full insight of information that is available in the real and digital world. If users need to seek out information, they sometimes lack the understanding to do so effectively—particularly when searching sources that are unfamiliar to them (e.g. governmental or internal databases as opposed to a well-known source such as Google).
Some technologies have attempted to enhance digital communications with continuous information retrieval and presentation solutions to provide related information to users in real time. For example, Grammarly continually accesses a database of grammar and spelling that provides suggestions to text. Similarly, All Are Green provides political information as specific terms, such as the names of political figures, are entered.
However, these typically rely upon a singular database, that is set up and edited by an external administrator, to which a user platform is linked. However, these have serious limitations in addressing user knowledge needs. Because they rely upon a single database with external control, such limited systems can satisfy only a singular knowledge need in an established domain (grammar, politics), and not necessary as completely, or in a way, a specific user may want. Extending the text recognition, content search, and information retrieval functions of these systems to increase or alter function or data is prohibitively cumbersome, requiring code creation from scratch, replication, and/or manipulation that cannot easily be performed by a typical user.
Because of the limited scope of these systems, a user can still have many data “blind spots” or simply not have the interactive control and retrieval of the types of data, or preferred sources, that would result in an optimal experience.
Accordingly, what is needed is an effective method and apparatus that can expand computer capabilities in such processing and retrieval through integration of these functions and needs, providing opportunities for increased insight that can be applied to their digital communications, which can render near-continuous processing and informing to enrich the relevance and accuracy of such digital communications.